Anonymization procedures for tabular data: an explanatory technical and legal synthesis

In the European Union, Data Controllers and Data Processors, who work with personal data, have to comply with the General Data Protection Regulation and other applicable laws. This affects the storing and processing of personal data. But some data processing in data mining or statistical analyses does not require any personal reference to the data. Thus, personal context can be removed. For these use cases, to comply with applicable laws, any existing personal information has to be removed by applying the so-called anonymization. However, anonymization should maintain data utility. Therefore, the concept of anonymization is a double-edged sword with an intrinsic trade-off: privacy enforcement vs. utility preservation. The former might not be entirely guaranteed when anonymized data are published as Open Data. In theory and practice, there exist diverse approaches to conduct and score anonymization. This explanatory synthesis discusses the technical perspectives on the anonymization of tabular data with a special emphasis on the European Union’s legal base. The studied methods for conducting anonymization, and scoring the anonymization procedure and the resulting anonymity are explained in unifying terminology. The examined methods and scores cover both categorical and numerical data. The examined scores involve data utility, information preservation, and privacy models. In practice-relevant examples, methods and scores are experimentally tested on records from the UCI Machine Learning Repository’s “Census Income (Adult)” dataset

Geographic information extraction from texts

A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction

The implications and impact of artificial intelligence, big data and HR analytics in HRM: A critical analysis of EU enterprises

This study offers a critical evaluation of HR analytics. Specifically, the ideas and concepts surrounding HR analytics, such as what is HR analytics, the development of HR analytics in organizations and how it may impact organizational performance. To advance and answer these research questions, this study relied on systematic reviews, logistic regression, interaction effect analysis, and interviews with the European Company Survey (ECS) to assess the interrelationship between HR analytics and organizational factors. Based on the findings, certain key areas are addressed. Firstly, research question 1 has succeeded in developing a more systematic and coherent definition of HR analytics and artificial intelligence in HR. It has also successfully identified some factors that influence the use of HR analytics in organisations. In particular, the results of study two found that factors such as firm age, firm size, the complexity of the firm process and the type of variable pay systems have been shown to be key indicators of why certain companies use HR analytics while others do not. Furthermore, the results for study three also provided a bigger picture of how organizational factors might be the reasons for explaining firms’ financial returns when examining the relationship between variables. In particular, factors such as employee motivation, the use of HR analytics, and variable pay systems are also believed to be critical in determining which factors affect a company’s financial returns. In addition, the study provides additional knowledge for five specific areas in analytics and artificial intelligence in HR, namely firm characteristics, challenges, key reasons to adopt HR software, new trends and user traits

Principles of Security and Trust

This open access book constitutes the proceedings of the 8th International Conference on Principles of Security and Trust, POST 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 10 papers presented in this volume were carefully reviewed and selected from 27 submissions. They deal with theoretical and foundational aspects of security and trust, including on new theoretical results, practical applications of existing foundational ideas, and innovative approaches stimulated by pressing practical problems

Principles of Security and Trust

This open access book constitutes the proceedings of the 8th International Conference on Principles of Security and Trust, POST 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2019. The 10 papers presented in this volume were carefully reviewed and selected from 27 submissions. They deal with theoretical and foundational aspects of security and trust, including on new theoretical results, practical applications of existing foundational ideas, and innovative approaches stimulated by pressing practical problems